Natural Language Instruction

Natural language instruction focuses on enabling artificial intelligence agents to understand and execute commands expressed in human language, aiming to bridge the gap between human communication and machine action. Current research emphasizes improving the robustness and accuracy of large language models (LLMs) in interpreting nuanced instructions, often employing techniques like chain-of-thought prompting, contrastive learning, and reinforcement learning to enhance performance across diverse tasks, including embodied AI and code generation. This field is significant for advancing human-computer interaction and enabling more intuitive control of complex systems in various domains, from robotics and data science to healthcare and software development.